Deep Learning for Incremental Object Detection and Visual Dialog
Dr. Shalini Ghosh is the Director of AI Research at the Artificial Intelligence Center of Samsung Research America, where she leads a group works on Situated AI and Multi-modal Learning (i.e., learning from computer vision, language, and speech). She has extensive experience and expertise in Machine Learning (ML), especially Deep Learning, and has worked on applications to multiple domains. Before joining Samsung Research, Dr. Ghosh was a Principal Computer Scientist in the Computer Science Laboratory at SRI International, where she has been the Principal Investigator/Tech Lead of several impactful DARPA and NSF projects. She was a Visiting Scientist at Google Research in 2014-2015, where she worked on applying deep learning (Google Brain) models to dialog systems and natural language applications. Dr. Ghosh has a Ph.D. in Computer Engineering from the University of Texas at Austin. She has won several grants and awards for her research, including a Best Paper award and a Best Student Paper Runner-up award for applications of ML to dependable computing. Dr. Ghosh is also on the program committee of multiple impactful conferences and journals in ML and AI (e.g., NIPS, ICML, KDD, AAAI), has served as invited panelist in multiple panels, and was invited to be a guest lecturer at UC Berkeley.